Observations are taken on net revenue from sales of a certain LCD TV at 50 retail outlets. The regression model was Y = net revenue (thousands of dollars), X1 = shipping cost (dollars per unit), X2 = expenditures on print advertising (thousands of dollars), X3 = expenditure on electronic media ads (thousands), X4 = rebate rate (percent of retail price).
(a) Write the fitted regression equation.
(b) Interpret each coefficient.
(c) Would the intercept be likely to have meaning in this regression?
(d) Use the fitted equation to make a prediction for NetRevenue when ShipCost = 10, PrintAds = 50, WebAds = 40, and Rebate% = 15.

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Predictor Coefficient Intercept ShipCost PrintAds WebAds Rebate% 4.306 -0.082 2.265 2.498 16.697